react-native-ai-skills
Provides integration recipes for the React Native AI @react-native-ai packages that wrap the Llama.rn (Llama.cpp), MLC-LLM, Apple Foundation backends. Use when integrating local on-device AI in React Native, setting up providers, model management.
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- 2026年7月23日 21:48
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SKILL.md
来源说明 · 只读预览- name
- react-native-ai-skills
- description
- Provides integration recipes for the React Native AI @react-native-ai packages that wrap the Llama.rn (Llama.cpp), MLC-LLM, Apple Foundation backends. Use when integrating local on-device AI in React Native, setting up providers, model management.
- license
- MIT
- metadata
- {"author":"Callstack","tags":"react-native, ai, llama, apple, mlc, ncnn, vercel-ai-sdk, on-device"}
# React Native AI Skills
## Overview
Example workflow for integrating on-device AI in React Native apps using the @react-native-ai ecosystem. Available provider tracks (can be combined):
- **Apple** – Apple Intelligence (iOS 26+)
- **Llama** – GGUF models via llama.rn
- **MLC** – MLC-LLM models
- **NCNN** – Low-level NCNN inference wrapper (vision, custom models)
## Path Selection Gate (Must Run First)
Before selecting any reference file, classify the user request:
1. Select **Apple**:
- if you intend to build with: `apple`, `Apple Intelligence`, `Apple Foundation Models`
- if you want features: `transcription`, `speech synthesis`, `embeddings` on Apple devices
- optionally with capabilities: tool calling
2. Select **Llama**:
- if you intend to use the following technologies: `llama`, `GGUF`, `llama.rn`, `HuggingFace`, `SmolLM`
- if you want to perform the following operations: `embedding model`, `rerank`, `speech model`
3. Select **MLC**:
- if you intend to use a library that allows for custom models and involves build-time model optimizations
4. Select **NCNN**:
- if you need to use run low-level inference on bare metal tensors
- if you intend to run inference of custom models such as convolutional networks, multi-layer perceptrons, low-level inference, etc.
- DO NOT select NCNN if the prompt mentions LLMs only, this use case is better solved by other providers
## Skill Format
Each reference file follows a strict execution format:
- Quick Command
- When to Use
- Prerequisites
- Step-by-Step Instructions
- Common Pitfalls
- Related Skills
Use the checklists exactly as written before moving to the next phase.
## When to Apply
Reference this package when:
- Integrating on-device AI in React Native apps
- Installing and configuring @react-native-ai providers
- Managing model downloads (llama, mlc)
- Wiring providers with Vercel AI SDK (generateText, streamText)
- Implementing SetupAdapter pattern for multi-provider apps
- Debugging native module or Expo plugin issues
## Priority-Ordered Guidelines
| Priority | Category | Impact | Start File |
| -------- | --------------------------- | ------ | -------------------------------- |
| 1 | Path selection and baseline | N/A | [quick-start][quick-start] |
| 2 | Apple provider | N/A | [apple-provider][apple-provider] |
| 3 | Llama provider | N/A | [llama-provider][llama-provider] |
| 4 | MLC-LLM provider | N/A | [mlc-provider][mlc-provider] |
| 5 | NCNN provider | N/A | [ncnn-provider][ncnn-provider] |
## Quick Reference
```bash
npm install
# Provider-specific install
npm add @react-native-ai/apple
npm add @react-native-ai/llama llama.rn
npm add @react-native-ai/mlc
npm add @react-native-ai/ncnn-wrapper
```
Route by path:
- Apple: [apple-provider][apple-provider]
- Llama: [llama-provider][llama-provider]
- MLC: [mlc-provider][mlc-provider]
- NCNN: [ncnn-provider][ncnn-provider]
## References
| File | Impact | Description |
| -------------------------------- | ------ | ------------------------------------------ |
| [quick-start][quick-start] | N/A | Shared preflight |
| [apple-provider][apple-provider] | N/A | Apple Intelligence setup and integration |
| [llama-provider][llama-provider] | N/A | GGUF models, llama.rn, model management |
| [mlc-provider][mlc-provider] | N/A | MLC models, download, prepare, Expo plugin |
| [ncnn-provider][ncnn-provider] | N/A | NCNN wrapper, loadModel, runInference |
## Problem → Skill Mapping
| Problem | Start With |
| ------------------------------------- | ---------------------------------------------- |
| Need path decision first | [quick-start][quick-start] |
| Integrate Apple Intelligence | [apple-provider][apple-provider] |
| Run GGUF models from HuggingFace | [llama-provider][llama-provider] |
| Run MLC-LLM models (Llama, Phi, Qwen) | [mlc-provider][mlc-provider] |
| Use NCNN for custom inference | [ncnn-provider][ncnn-provider] |
| Multi-provider app with SetupAdapter | [quick-start][quick-start] → provider-specific |
| Expo + native module setup | Provider-specific (each has Expo notes) |
[quick-start]: references/quick-start.md
[apple-provider]: references/apple-provider.md
[llama-provider]: references/llama-provider.md
[mlc-provider]: references/mlc-provider.md
[ncnn-provider]: references/ncnn-provider.md
---
> Source: [callstackincubator/ai](https://github.com/callstackincubator/ai) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-28 -->
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